Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Je-Yeon Yun; Premika S W Boedhoe; Chris Vriend; Damiaan Denys; D.J. Stein; O.A. Van den Heuvel; Jun Soo Kwon

doi:10.1093/brain/awaa001

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Je-Yeon Yun, Premika S W Boedhoe, Chris Vriend, , Damiaan Denys, D.J. Stein, O.A. Van den Heuvel, Jun Soo Kwon

Netherlands Institute for Neuroscience (NIN)

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

98 Citations (Scopus)

484 Downloads (Pure)

Abstract

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Original language	English
Pages (from-to)	684-700
Number of pages	17
Journal	Brain
Volume	143
Issue number	2
DOIs	https://doi.org/10.1093/brain/awaa001
Publication status	Published - 2020

Access to Document

10.1093/brain/awaa001

Yun2020Final published version, 1.28 MB

Cite this

@article{057ae541424e4eb19174bfe92ecaf08a,

title = "Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium",

abstract = "Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.",

author = "Je-Yeon Yun and Boedhoe, {Premika S W} and Chris Vriend and Neda Jahanshad and Yoshinari Abe and Ameis, {Stephanie H} and Alan Anticevic and Arnold, {Paul D} and Batistuzzo, {Marcelo C} and Francesco Benedetti and Beucke, {Jan C} and Irene Bollettini and Anushree Bose and Silvia Brem and Anna Calvo and Yuqi Cheng and Cho, {Kang Ik K} and Valentina Ciullo and Sara Dallaspezia and Damiaan Denys and Feusner, {Jamie D} and Jean-Paul Fouche and M{\`o}nica Gim{\'e}nez and Patricia Gruner and Hibar, {Derrek P} and Hoexter, {Marcelo Q} and Hao Hu and Chaim Huyser and Keisuke Ikari and Norbert Kathmann and Christian Kaufmann and Kathrin Koch and Luisa Lazaro and Christine Lochner and Paulo Marques and Rachel Marsh and Ignacio Mart{\'i}nez-Zalaca{\'i}n and David Mataix-Cols and Mench{\'o}n, {Jos{\'e} M} and Luciano Minuzzi and Pedro Morgado and Pedro Moreira and Takashi Nakamae and Tomohiro Nakao and Narayanaswamy, {Janardhanan C} and Nurmi, {Erica L} and Joseph O'Neill and John Piacentini and Fabrizio Piras and Federica Piras and D.J. Stein and {Van den Heuvel}, O.A. and Kwon, {Jun Soo}",

note = "{\textcopyright} The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.",

year = "2020",

doi = "10.1093/brain/awaa001",

language = "English",

volume = "143",

pages = "684--700",

journal = "Brain",

issn = "0006-8950",

publisher = "Oxford University Press",

number = "2",

}

TY - JOUR

T1 - Brain structural covariance networks in obsessive-compulsive disorder

T2 - a graph analysis from the ENIGMA Consortium

AU - Yun, Je-Yeon

AU - Boedhoe, Premika S W

AU - Vriend, Chris

AU - Jahanshad, Neda

AU - Abe, Yoshinari

AU - Ameis, Stephanie H

AU - Anticevic, Alan

AU - Arnold, Paul D

AU - Batistuzzo, Marcelo C

AU - Benedetti, Francesco

AU - Beucke, Jan C

AU - Bollettini, Irene

AU - Bose, Anushree

AU - Brem, Silvia

AU - Calvo, Anna

AU - Cheng, Yuqi

AU - Cho, Kang Ik K

AU - Ciullo, Valentina

AU - Dallaspezia, Sara

AU - Denys, Damiaan

AU - Feusner, Jamie D

AU - Fouche, Jean-Paul

AU - Giménez, Mònica

AU - Gruner, Patricia

AU - Hibar, Derrek P

AU - Hoexter, Marcelo Q

AU - Hu, Hao

AU - Huyser, Chaim

AU - Ikari, Keisuke

AU - Kathmann, Norbert

AU - Kaufmann, Christian

AU - Koch, Kathrin

AU - Lazaro, Luisa

AU - Lochner, Christine

AU - Marques, Paulo

AU - Marsh, Rachel

AU - Martínez-Zalacaín, Ignacio

AU - Mataix-Cols, David

AU - Menchón, José M

AU - Minuzzi, Luciano

AU - Morgado, Pedro

AU - Moreira, Pedro

AU - Nakamae, Takashi

AU - Nakao, Tomohiro

AU - Narayanaswamy, Janardhanan C

AU - Nurmi, Erica L

AU - O'Neill, Joseph

AU - Piacentini, John

AU - Piras, Fabrizio

AU - Piras, Federica

AU - Stein, D.J.

AU - Van den Heuvel, O.A.

AU - Kwon, Jun Soo

PY - 2020

Y1 - 2020

N2 - Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

AB - Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

U2 - 10.1093/brain/awaa001

DO - 10.1093/brain/awaa001

M3 - Article

C2 - 32040561

SN - 0006-8950

VL - 143

SP - 684

EP - 700

JO - Brain

JF - Brain

IS - 2

ER -

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Abstract

Access to Document

Fingerprint

Cite this